caa a22 4500 445350598 CHVBK 20180317142842.0 cr unu---uuuuu 170323e20111001xx s 000 0 eng 10.1007/s00221-011-2850-5 doi (NATIONALLICENCE)springer-10.1007/s00221-011-2850-5 Anatomically constrained minimum variance beamforming applied to EEG [Elektronische Daten] [Vyacheslav Murzin, Armin Fuchs, J. Kelso] Neural activity as measured non-invasively using electroencephalography (EEG) or magnetoencephalography (MEG) originates in the cortical gray matter. In the cortex, pyramidal cells are organized in columns and activated coherently, leading to current flow perpendicular to the cortical surface. In recent years, beamforming algorithms have been developed, which use this property as an anatomical constraint for the locations and directions of potential sources in MEG data analysis. Here, we extend this work to EEG recordings, which require a more sophisticated forward model due to the blurring of the electric current at tissue boundaries where the conductivity changes. Using CT scans, we create a realistic three-layer head model consisting of tessellated surfaces that represent the cerebrospinal fluid-skull, skull-scalp, and scalp-air boundaries. The cortical gray matter surface, the anatomical constraint for the source dipoles, is extracted from MRI scans. EEG beamforming is implemented on simulated sets of EEG data for three different head models: single spherical, multi-shell spherical, and multi-shell realistic. Using the same conditions for simulated EEG and MEG data, it is shown (and quantified by receiver operating characteristic analysis) that EEG beamforming detects radially oriented sources, to which MEG lacks sensitivity. By merging several techniques, such as linearly constrained minimum variance beamforming, realistic geometry forward solutions, and cortical constraints, we demonstrate it is possible to localize and estimate the dynamics of dipolar and spatially extended (distributed) sources of neural activity. Springer-Verlag, 2011 Electroencephalography nationallicence EEG nationallicence Source reconstruction nationallicence Inverse problem nationallicence Beamforming nationallicence Boundary element method nationallicence Murzin Vyacheslav Center for Complex Systems and Brain Sciences, Florida Atlantic University, 33431, Boca Raton, FL, USA aut Fuchs Armin Center for Complex Systems and Brain Sciences, Florida Atlantic University, 33431, Boca Raton, FL, USA aut Kelso J. Center for Complex Systems and Brain Sciences, Florida Atlantic University, 33431, Boca Raton, FL, USA aut Experimental Brain Research Springer-Verlag 214/4(2011-10-01), 515-528 0014-4819 214:4<515 2011 214 221 https://doi.org/10.1007/s00221-011-2850-5 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s00221-011-2850-5 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Murzin Vyacheslav Center for Complex Systems and Brain Sciences, Florida Atlantic University, 33431, Boca Raton, FL, USA aut NATIONALLICENCE 700 1- Fuchs Armin Center for Complex Systems and Brain Sciences, Florida Atlantic University, 33431, Boca Raton, FL, USA aut NATIONALLICENCE 700 1- Kelso J. Center for Complex Systems and Brain Sciences, Florida Atlantic University, 33431, Boca Raton, FL, USA aut NATIONALLICENCE 773 0- Experimental Brain Research Springer-Verlag 214/4(2011-10-01), 515-528 0014-4819 214:4<515 2011 214 221 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer